Key Test Automation Metrics in Agile Testing

Why test metrics?

• Visibility. Test automation metrics can help to solve QA visibility problems. Metrics can provide a high-level overview of the testing process by aggregating key test automation data such as test cases quantity, test execution time, automation error patterns.
• A Way to improve. Test automation metrics can help to improve QA processes. Metrics can enable an organization to filter out ineffectiveness and improve over time. If you cannot measure it, you’ll not be able to improve it.
• Decision making. Test automation metrics can help decision makers to get a better understanding of the product quality and what should be done next.

Test Automation Coverage.

This metric illustrates the percentage of tests executed automatically compared to those done manually.

Metric Value: It helps to track whether a QA team is meeting automated test coverage goals, or not. In the Agile methodology test automation coverage should increase sprint to sprint.

Test Automation Progress.

This metric shows the ratio of automated test cases to the automatable test cases over the time.

Metric Value: It helps to understand the progress and pace of test automation compared to the plans and discover test automation problems on the early stage if deviations are detected. It also shows how well QA engineers respond to the objective of automated software testing and if such objectives were right.

Automatable Test Cases.

Understanding the percentage of test cases automatable compared to the total test cases number is very helpful in formulating an appropriate testing strategy and keeping a balance between automated and manual testing.

Metric Value: This metric can help to determine the priorities in the QA processes and focus on the most important test cases first.

Automation Script Effectiveness.

An evaluation of defects found via automated testing compared to the total number of acceptable defects is an Automation Script Effectiveness.

Metric Value: It allows us to see the problems with test automation quality. Having a low percentage of Automation Script Effectiveness indicates that there might be problems with automation suite quality.

Automated Test Pass Rate.

It measures how many automated tests have passed vs. how many have failed.

Metric Value: It helps to understand the stability of the automation suite as well as its effectiveness. Having a low failure rate indicates that the script logic is correct, while a low pass rate requires an effort validating failures. Also it raises a question if those failures occurred because of the flaky test cases or they discovered issues with the software. However, it’s important to understand that the metric cannot show the quality of those tests passed.

Build Stability.

When test automation suites are a part of software building pipelines in a CI/CD this metric can demonstrate the efficacy of the tests by calculating the ratio of failed builds to passed ones.

Metric Value: This metric gives an idea whether the tests implemented are sufficient to ensure a stable build process.

Conclusions

Test automation has become an integrated part of the agile testing processes as well as CI/CD pipelines so that many companies found it beneficial to invest time and effort to set up proper test automation processes.

Test automation metrics help QA teams to evaluate testing strategy promptly and make appropriate adjustments, resulting in better quality software.

In qaVisor, we focus on high-quality QA services by having experienced QA engineers in the team and providing the appropriate metrics to ensure quality assurance processes develop in the right direction.